{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据探索\n",
    "\n",
    "数据说明：  \n",
    "Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集） 根据现有的医疗信息预测5年内皮马印第安人糖尿病发作的概率。   \n",
    "\n",
    "数据集共9个字段: \n",
    "* 0列为pregnants(怀孕次数)；\n",
    "* 1列为Plasma_glucose_concentration(口服葡萄糖耐量试验中2小时后的血浆葡萄糖浓度)；\n",
    "* 2列为blood_pressure(舒张压,单位:mm Hg）\n",
    "* 3列为Triceps_skin_fold_thickness(三头肌皮褶厚度,单位：mm）\n",
    "* 4列为serum_insulin(餐后血清胰岛素,单位:mm）\n",
    "* 5列为BMI,体重指数（体重（公斤）/ 身高（米）^2）\n",
    "* 6列为Diabetes_pedigree_function(糖尿病家系作用)\n",
    "* 7列为Age(年龄)\n",
    "* 8列为Target(分类变量,0或1）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入工具\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "0          6                           148              72   \n",
       "1          1                            85              66   \n",
       "2          8                           183              64   \n",
       "3          1                            89              66   \n",
       "4          0                           137              40   \n",
       "\n",
       "   Triceps_skin_fold_thickness  serum_insulin   BMI  \\\n",
       "0                           35              0  33.6   \n",
       "1                           29              0  26.6   \n",
       "2                            0              0  23.3   \n",
       "3                           23             94  28.1   \n",
       "4                           35            168  43.1   \n",
       "\n",
       "   Diabetes_pedigree_function  Age  Target  \n",
       "0                       0.627   50       1  \n",
       "1                       0.351   31       0  \n",
       "2                       0.672   32       1  \n",
       "3                       0.167   21       0  \n",
       "4                       2.288   33       1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读入原始数据\n",
    "train = pd.read_csv(\"pima-indians-diabetes.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "pregnants                       768 non-null int64\n",
      "Plasma_glucose_concentration    768 non-null int64\n",
      "blood_pressure                  768 non-null int64\n",
      "Triceps_skin_fold_thickness     768 non-null int64\n",
      "serum_insulin                   768 non-null int64\n",
      "BMI                             768 non-null float64\n",
      "Diabetes_pedigree_function      768 non-null float64\n",
      "Age                             768 non-null int64\n",
      "Target                          768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "# 查看数据基本信息\n",
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "count  768.000000                    768.000000      768.000000   \n",
       "mean     3.845052                    120.894531       69.105469   \n",
       "std      3.369578                     31.972618       19.355807   \n",
       "min      0.000000                      0.000000        0.000000   \n",
       "25%      1.000000                     99.000000       62.000000   \n",
       "50%      3.000000                    117.000000       72.000000   \n",
       "75%      6.000000                    140.250000       80.000000   \n",
       "max     17.000000                    199.000000      122.000000   \n",
       "\n",
       "       Triceps_skin_fold_thickness  serum_insulin         BMI  \\\n",
       "count                   768.000000     768.000000  768.000000   \n",
       "mean                     20.536458      79.799479   31.992578   \n",
       "std                      15.952218     115.244002    7.884160   \n",
       "min                       0.000000       0.000000    0.000000   \n",
       "25%                       0.000000       0.000000   27.300000   \n",
       "50%                      23.000000      30.500000   32.000000   \n",
       "75%                      32.000000     127.250000   36.600000   \n",
       "max                      99.000000     846.000000   67.100000   \n",
       "\n",
       "       Diabetes_pedigree_function         Age      Target  \n",
       "count                  768.000000  768.000000  768.000000  \n",
       "mean                     0.471876   33.240885    0.348958  \n",
       "std                      0.331329   11.760232    0.476951  \n",
       "min                      0.078000   21.000000    0.000000  \n",
       "25%                      0.243750   24.000000    0.000000  \n",
       "50%                      0.372500   29.000000    0.000000  \n",
       "75%                      0.626250   41.000000    1.000000  \n",
       "max                      2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看数据统计信息\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于数据中的1-5列，0没用意义，应该是缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plasma_glucose_concentration      5\n",
      "blood_pressure                   35\n",
      "Triceps_skin_fold_thickness     227\n",
      "serum_insulin                   374\n",
      "BMI                              11\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "NaN_col_names = ['Plasma_glucose_concentration','blood_pressure','Triceps_skin_fold_thickness','serum_insulin','BMI']\n",
    "print((train[NaN_col_names] == 0).sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "第1、2、5列中0值较少；相比较而言，第3、4列中的0值多出数倍，接近总量的一半。 为了确保有足够的数据量来训练模型，针对不同的列需要有不同的缺失值判断策略。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看数据类别分布（直方图）\n",
    "sns.countplot(train['Target'])\n",
    "plt.xlabel('Diabetes')\n",
    "plt.ylabel('Number of occurrences')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 怀孕次数pregnants（直方图）\n",
    "sns.countplot(train['pregnants'])\n",
    "plt.xlabel('Number of pregnants')\n",
    "plt.ylabel('Number of occurrences')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 怀孕次数pregnants（按Target分类直方图）\n",
    "sns.countplot(x=\"pregnants\", hue=\"Target\",data=train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 口服葡萄糖耐量试验中2小时后的血浆葡萄糖浓度Plasma_glucose_concentration\n",
    "sns.distplot(train.Plasma_glucose_concentration, kde = True)\n",
    "plt.xlabel('Plasma_glucose_concentration')\n",
    "plt.ylabel('Number of occurrences')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 血糖与分类关系\n",
    "sns.violinplot(x='Target', y='Plasma_glucose_concentration', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('Plasma_glucose_concentration', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 血压blood_pressure\n",
    "sns.distplot(train.blood_pressure, kde = True)\n",
    "plt.xlabel('blood_pressure')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 血压与分类关系\n",
    "sns.violinplot(x='Target', y='blood_pressure', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('blood_pressure', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 三头肌皮褶厚度（单位：mm）：Triceps_skin_fold_thickness\n",
    "sns.distplot(train.Triceps_skin_fold_thickness, kde = True)\n",
    "plt.xlabel('Triceps_skin_fold_thickness')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 三头肌皮褶厚度与分类关系\n",
    "sns.violinplot(x='Target', y='Triceps_skin_fold_thickness', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('Triceps_skin_fold_thickness', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 餐后血清胰岛素（单位:mm）：serum_insulin\n",
    "sns.distplot(train.serum_insulin, kde = True)\n",
    "plt.xlabel('serum_insulin')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 餐后血清胰岛素与分类关系\n",
    "sns.violinplot(x='Target', y='serum_insulin', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('serum_insulin', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 体重指数（体重（公斤）/ 身高（米）^2）：BMI\n",
    "sns.distplot(train.BMI, kde = True)\n",
    "plt.xlabel('BMI')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 体重指数与分类关系\n",
    "sns.violinplot(x='Target', y='BMI', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('BMI', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 糖尿病家系作用：Diabetes_pedigree_function\n",
    "sns.distplot(train.Diabetes_pedigree_function, kde = True)\n",
    "plt.xlabel('Diabetes_pedigree_function')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 糖尿病家系作用：分类堆积图\n",
    "DF = train.groupby(['Diabetes_pedigree_function', 'Target'])['Diabetes_pedigree_function'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind='bar', stacked=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 年龄：Age\n",
    "sns.distplot(train.Age, kde = True)\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 年龄与分类关系\n",
    "sns.violinplot(x='Target', y='Age', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('Age', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 特征之间的相关性\n",
    "data_corr = train.corr().abs()\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# 将1-5列数据中的0值转换为NaN\n",
    "NaN_col_names = ['Plasma_glucose_concentration','blood_pressure','Triceps_skin_fold_thickness','serum_insulin','BMI']\n",
    "train[NaN_col_names] = train[NaN_col_names].replace(0, np.NaN)\n",
    "print(train.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 对缺失值较多的特征，新增一个特征，表示这个特征是否缺失\n",
    "train['Triceps_skin_fold_thickness_Missing'] = train['Triceps_skin_fold_thickness'].apply(lambda x: 1 if pd.isnull(x) else 0)\n",
    "train[['Triceps_skin_fold_thickness','Triceps_skin_fold_thickness_Missing']].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['serum_insulin_Missing'] = train['serum_insulin'].apply(lambda x: 1 if pd.isnull(x) else 0)\n",
    "train[['serum_insulin','serum_insulin_Missing']].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 缺失值与分类关系\n",
    "sns.countplot(x=\"Triceps_skin_fold_thickness_Missing\", hue=\"Target\",data=train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.countplot(x=\"serum_insulin_Missing\", hue=\"Target\",data=train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 缺失值与分类无太多关系，先删除\n",
    "train.drop([\"Triceps_skin_fold_thickness_Missing\", \"serum_insulin_Missing\"], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 原数据中的缺失值用中值替代\n",
    "medians = train.median() \n",
    "train = train.fillna(medians)\n",
    "print(train.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据标准化\n",
    "\n",
    "# 分离特征和标签\n",
    "y_train = train['Target']   \n",
    "X_train = train.drop([\"Target\"], axis=1)\n",
    "\n",
    "# 保存特征列名，标准化后重新构建数据集\n",
    "feat_names = X_train.columns\n",
    "\n",
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# 初始化特征的标准化器\n",
    "ss_X = StandardScaler()\n",
    "\n",
    "# 对特征数据标准化\n",
    "X_train = ss_X.fit_transform(X_train)\n",
    "\n",
    "# 保存标准化后的数据\n",
    "X_train = pd.DataFrame(columns = feat_names, data = X_train)\n",
    "train = pd.concat([X_train, y_train], axis = 1)\n",
    "train.to_csv('FE_pima-indians-diabetes.csv',index = False,header=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 交叉验证与调优"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读入数据\n",
    "train = pd.read_csv(\"FE_pima-indians-diabetes.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 准备数据\n",
    "y_train = train['Target']   \n",
    "X_train = train.drop([\"Target\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 准备调优参数\n",
    "penaltys = ['l1','l2']\n",
    "Cs = [0.001, 0.01, 0.1, 1, 10, 100, 1000]\n",
    "tuned_parameters = dict(penalty = penaltys, C = Cs)\n",
    "lr_penalty= LogisticRegression(solver='liblinear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# log似然损失调优\n",
    "grid= GridSearchCV(lr_penalty, tuned_parameters,cv=5, scoring='neg_log_loss')\n",
    "grid.fit(X_train,y_train)\n",
    "print(-grid.best_score_)\n",
    "print(grid.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 正确率调优\n",
    "grid= GridSearchCV(lr_penalty, tuned_parameters,cv=5, scoring='accuracy')\n",
    "grid.fit(X_train,y_train)\n",
    "print(-grid.best_score_)\n",
    "print(grid.best_params_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从调优结果看，使用不同的评分方法，选到的正则相和超参数也不同，实际应用中需选择适合的评分方法；"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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